Wavelet transform is a way of multi-resolution image transform which is often used for image compression. Applications of wavelet transform include transform coding in JPEG2000 standard. The objective of wavelet transform is to represent an original full image by a part of the full image, and the original image can be obtained by utilizing a low-resolution image (a part of the original image) and some discrepant features required for restoration of the original full image. A lifting scheme is an effective implementation of wavelet transform and a flexible tool for constructing wavelets. FIG. 1 shows a typical structure for encoding and decoding original images by means of 1D data. The left side thereof corresponds to an encoder, and the right side thereof corresponds to a decoder. The encoder compresses an image by using a prediction filter p and an update filter u to obtain a low-resolution image A and details D. During the compression application, the desired value of D is about 0 such that most information can be contained in the image A. During the decompression, the same update filter u and predication filter p are used but arranged in a reverse order. It is easy to prove that such an arrangement renders output equal to input, with no requirement on the filters p and u. Generally speaking, filtering parameters in each filtering unit of such filters p and u are manually set, and the weight set in such a manner can hardly enable the corresponding encoder to obtain an optimal or approximately optimal compression rate, and the manual setting procedure is very complicated and error-prone.